Case Study: Microsoft Office 365

“DataStax Enterprise on Azure enables us to do everything we needed, including near-real-time data processing and longer-term batch processes. We’re also able to handle linear data growth without having to shard our clusters and manually manage data.”

Sean UsherSenior Software EngineerCustomer Fabrics PlatformMicrosoft

Microsoft is improving the Office 365 experience for millions of customers with DataStax Enterprise on Azure.

Industry: Technology

Millions of businesses worldwide use open source technology, and Microsoft is no exception. In fact, one in three Azure Virtual Machines runs Linux, and Microsoft is taking advantage of open source technologies to enhance its own cloud services. For example, the Customer Fabrics Platform Team at Microsoft recently chose DataStax Enterprise—the always-on data platform for cloud applications powered by the best distribution of Apache Cassandra™ — to improve service across multiple areas. Now, administrators work with DataStax Enterprise to gain insight into user behavior. Results include better support for Microsoft’s fastest-selling product, and more satisfied, productive customers.

Opportunity

Tap into more than 300 terabytes of anonymized data from client and server logs to gain user behavior insights.

Solution

An always-on data platform that can scale quickly to handle an influx of information from every Office 365 server and client device.

The combined power and resilience of a comprehensive real-time data platform with the big data analytics capabilities of Apache Spark™.

Running on Azure Virtual Machines with the Linux Ubuntu operating system, the solution uses the distributed streaming platform Apache Kafka™ to ingest data from Office 365 servers and client devices. Then information flows into DSE’s Spark and Cassandra. The platform generates datasets that can be widely used for analytics, and it streams data for near-real-time consumption.

Results

Reduced support tickets. By targeting both server-side and client-side log data, the team could determine if a problem originated internally or from tenant administrators and solve problems before they escalated.

Faster fixes. Administrators can see if users make multiple attempts to file a support ticket, indicating that either the page isn’t working or needs to be redesigned.

Proactive customer support. They can identify which users are affected by a service incident and proactively contact them.